Hi I have a data set consisting of pictures on which individual plants were identified and categorized into "alive", "dead" and "unknown" if it was not clear. The time of these pictures ranges from 1937 to today and the intervals range between 13 and 1 year.
I am trying to get an understanding of the mortality rate which I can then use in an individual based model. Therefore I thought of using survival analysis. I have ordered my data in the required format, and classified the events as "interval censored" (event=3) for the cases where the plant died and "right censored" (event=0) but I have still a problem I managed to obtain a Surv() object by calling > surv <- with(survival, Surv(time, time2, event, type="interval")) where survival is my dataset > surv [1] [13, 16] 68+ 16+ 68+ 68+ 68+ [26, 34] 68+ [9] 68+ 16+ [54, 58] [64, 67] 68+ [34, 54] [34, 54] [58, 63] [17] [48, 58] [48, 63] [34, 54] And it looks correct (I set the year 1937 to 0) But where to from here? I understand that most of the analysis can not be done with interval censored data? As far as I understand it, I have to use interval censored as the observation intervals are not equal and in addition quite large. The data is from one site, no interference. As I said, I would like to have an estimate of the hazard function (I guess) to get information about the mortality rate of the individuals. Any help welcome, Rainer -- NEW EMAIL ADDRESS AND ADDRESS: [EMAIL PROTECTED] [EMAIL PROTECTED] WILL BE DISCONTINUED END OF MARCH Rainer M. Krug, Dipl. Phys. (Germany), MSc Conservation Biology (UCT) Leslie Hill Institute for Plant Conservation University of Cape Town Rondebosch 7701 South Africa Fax: +27 - (0)86 516 2782 Fax: +27 - (0)21 650 2440 (w) Cell: +27 - (0)83 9479 042 Skype: RMkrug email: [EMAIL PROTECTED] [EMAIL PROTECTED] ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.